Master Data Manager

SAP Basis Engineer

Manager, Data Engineering

Sr. Software Engineer - Ag & Trading .Net

Data Engineer, Senior

Senior Data Scientist - Machine Learning

VP - Payment Analytics

Manager, Quality Assurance - Digital Analytics (L09)

AVP – Model Ops Engineer

Senior Software Engineer 1 (.Net)

Role Description: <ul><li>The Master Data Manager will join the Business Unit’s Digital, Data &amp; Technology (DD&amp;T) organization and report directly to the Chief Information Officer (CIO), Industrial &amp; Commercial Transportation (ICT). As part of DD&amp;T, this role is a key enabler of operational excellence, digital transformation, and AI readiness.</li><li>The Master Data Manager will coordinate cross-functional Master Data Owners, define and track data quality KPIs, and ensure master data issues are corrected in a sustainable and scalable manner.</li><li>Rather than executing transactional data maintenance, this role orchestrates standards, transparency, and accountability across the Business Unit, ensuring master data supports business processes, process intelligence, and AI-driven initiatives.</li></ul> Responisbilities: 1. Master Data Governance &amp; Coordination <ul><li>Establish and operationalize a ICT Master Data Governance framework.</li><li>Coordinate nominated Master Data Owners across functions (Operations, Engineering, Finance, Project Management, Commercial, Product Management, etc.).</li><li>Define clear roles, responsibilities, and escalation paths for data ownership.</li><li>Facilitate recurring cross-functional data governance forums and reviews.</li></ul> 2. Data Quality KPI Definition &amp; Monitoring <ul><li>Define measurable KPIs for data accuracy, completeness, consistency, timeliness, and integrity.</li><li>Implement dashboards (in collaboration with DD&amp;T teams) to monitor data health across systems (SAP S/4HANA, Hydra MES, Planisware, Salesforce, SAP IBP).</li><li>Establish target thresholds and continuous improvement plans.</li><li>Ensure transparency of data quality performance to functional leadership.</li></ul> 3. Sustainable Issue Resolution <ul><li>Identify systemic root causes of master data defects.</li><li>Drive sustainable corrective actions with Master Data Owners and process stakeholders.</li><li>Ensure data issues are resolved at process level, not through recurring manual corrections.</li><li>Partner with DD&amp;T Process Automation &amp; Process Intelligence teams to eliminate recurring data.</li></ul> 4. Enable AI &amp; Process Intelligence <ul><li>Ensure master data structures and governance support:</li><li>Advanced analytics and AI use cases</li><li>Process mining and task mining initiatives</li><li>Reliable automation and digital workflows</li><li>Collaborate with the DD&amp;T AI Lab to ensure master data is AI-ready and supports model performance.</li><li>Support data standardization to enable reuse of models and interoperability across functions.</li></ul> 5. Transformation &amp; Continuous Improvement <ul><li>Promote data as a strategic asset within the Business Unit.</li><li>Drive adoption of standardized templates, definitions, and taxonomies.</li><li>Support SAP S/4HANA evolution and system integrations from a data governance perspective.</li><li>Contribute to digital transformation programs by embedding data quality controls early in process design.</li></ul> Requirements: <ul><li>Bachelor’s degree in Engineering, Supply Chain, Information Systems, Business, or related field.</li><li>5+ years of experience in Master Data Management, Data Governance, ERP environments, or cross-functional process management.</li><li>Experience working in global, cross-functional manufacturing or industrial environments.</li><li>Strong understanding of ERP systems (SAP S/4HANA preferred) and enterprise data flows.</li><li>Experience defining and tracking data quality KPIs.</li><li>Knowledge of data analytics environments (e.g., Databricks) is a plus.</li><li>Strong facilitation, stakeholder management, and influencing skills.</li></ul>

Responsibilities: <ul><li>Designs, builds, and supports SAP platform solutions by applying sound engineering practices to ensure system stability, performance, and scalability.</li><li>Utilizes enterprise tools and methodologies to automate system deployments, transport, and administrative activities, enabling reliable and repeatable releases.</li><li>Collaborate with cross‑functional partners to translate moderately complex business and technical requirements into effective SAP Basis solutions.</li><li>Performs system validation, technical testing, monitoring, and troubleshooting to maintain the quality and availability of SAP systems.</li><li>Contributes to continuous improvement initiatives by identifying opportunities to enhance SAP Basis processes, automation, and operational efficiency.</li><li>Creates and maintains clear technical documentation for SAP landscapes, configurations, and operational procedures.</li><li>Provides technical support for moderately complex SAP Basis issues, ensuring timely resolution and minimal impact to business operations.</li><li>Drives automation and quality through the use of enterprise testing and deployment tools, including Tosca for test automation and qTest for test management, execution, and traceability.</li><li>Develops, executes, and maintains manual and automated test assets for SAP systems, ensuring end‑to‑end coverage across SIT, UAT, regression, and integration testing cycles.</li><li>Performs system validation, monitoring, defect analysis, and troubleshooting in partnership with development, security, and infrastructure teams to ensure reliability and performance.</li></ul> Requirements: <ul><li>Minimum requirement of 5 years of relevant work experience with SAP Basis.&nbsp;</li><li>Demonstrated expertise in SAP Basis engineering, with strong knowledge of SAP system architecture, technical landscape design, system administration, upgrades, transport, performance monitoring, and operational support across multiple SAP environments.</li><li>Experience managing and supporting SAP technical operations, including system availability, batch processing, interfaces, background jobs, monitoring, troubleshooting, and incident resolution in alignment with enterprise service expectations.</li><li>Proven ability to support SAP Fiori and UI technical components from a Basis perspective, including configuration, activation, performance support, and coordination with security and application teams.</li><li>Experience leveraging scripting and technical tools (such as SQL and automation utilities) to improve operational efficiency, support system analysis, and standardize SAP Basis activities.</li><li>Working knowledge of cloud‑hosted and hybrid SAP landscapes, including experience supporting SAP systems on platforms such as Microsoft Azure, AWS, or Google Cloud, with an understanding of infrastructure, connectivity, and platform operations.</li></ul>

Responsibilities: <ul><li>DATA &amp; ANALYTICAL SOLUTIONS: Oversees the development of data products and solutions using big data and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust.</li><li>DATA PIPELINES: Develops and monitors streaming and batch data pipelines that facilitate the seamless ingestion of data from various data sources, transform the data into information and move to data stores like data lake, data warehouse and others.</li><li>DATA SYSTEMS: Reviews existing data systems and architectures to lead identification of areas for improvement and optimization.</li><li>DATA INFRASTRUCTURE: Oversees the preparation of data infrastructure to drive the efficient storage and retrieval of data.</li><li>DATA FORMATS: Reviews and resolves appropriate data formats to improve data usability and accessibility across the organization.</li><li>STAKEHOLDER MANAGEMENT: Partners collaboratively with multi-functional data and advanced analytic teams to capture requirements and ensure that data solutions meet the functional and non-functional needs of various partners.</li><li>DATA FRAMEWORKS: Builds complex prototypes to test new concepts and provides guidance to implement data engineering frameworks and architectures that improve data processing capabilities and support advanced analytics initiatives.</li><li>AUTOMATED DEPLOYMENT PIPELINES: Oversees the development of automated deployment pipelines improving efficiency of code deployments with fit for purpose governance.</li><li>DATA MODELING: Guides the team to perform data modeling in accordance to the datastore technology to ensure sustainable performance and accessibility.</li><li>TEAM MANAGEMENT: Manages team members to achieve the organizations goals, by ensuring productivity, communicating performance expectations, creating goal alignment, giving and seeking feedback, providing coaching, measuring progress and holding people accountable, supporting employee development, recognizing achievement and lessons learned, and developing enabling conditions for talent to thrive in an inclusive team culture.</li></ul> Requirements: <ul><li>Some experience in React, including hooks, context API, and state management libraries (Redux, Zustand)</li><li>Solid experience with JavaScript (ES6+), TypeScript, HTML5, CSS3.</li><li>Strong experience with C# and .NET Framework/.NET Core.</li><li>Solid understanding of object-oriented programming.</li><li>Experience with unit testing and mocking frameworks (e.g., xUnit, NUnit, Moq).</li><li>Familiarity with design patterns (e.g., Repository, Factory, Strategy).</li><li>Experience with SQL DBs, MySQL, Postgres, or MS SQL: writing queries, stored procedures, and performancetuning.</li><li>Knowledge of RESTful APIs and message-based systems.</li><li>Experience with relational databases and data access libraries (e.g., Entity Framework, Dapper).</li><li>Knowledge of ReactJS</li><li>Proficient in Git: branching, merging, pull requests, and version control workflows.</li></ul>

Responsibilities: <ul><li>Demonstrate accountability by ensuring timely and high-quality project delivery.</li><li>Be result driven, consistently achieving measurable outcomes and meeting goals.</li><li>Act as a team player, collaborating effectively with cross-functional teams.</li><li>Exhibit a can-do mentality, tackling challenges with a proactive and positive approach.</li><li>Apply software engineering patterns and principles to design, develop, test, integrate, maintain, troubleshoot and document complex and varied software solutions and incorporate security practices in newly developed and maintained applications.</li><li>Participate in peer code review sessions to review code, coach peers and ensure code quality.</li><li>Take the lead in the assigned agile team to adopt agile philosophies, facilitate agile ceremonies and identify continuous improvement opportunities.</li><li>Incorporate the companys engineering and development best practices within the full software development lifecycle including coding standards, code reviews, source control management, building processes, testing and security principles, to deliver high quality code rapidly.</li><li>Collaborate to lead demonstration and continuous feedback sessions to improve development and help drive the long term vision.</li><li>Participate in the engineering community by maintaining and sharing relevant technical approaches and modern skills.</li><li>Independently handle complex issues with minimal supervision, while escalating only the most complex issues to appropriate staff.</li><li>Other duties as assigned</li></ul> Requirements: <ul><li>Bachelor’s degree in a related field or equivalent experience</li><li>Confirmed experience automating pipelines for continuous integration, testing, delivery and security.</li><li>Confirmed experience architecting applications, databases, services or integrations.</li><li>Extensive experience with .NET Framework and .NET Core.</li><li>Familiarity with front-end technologies like HTML, CSS, JavaScript, and frameworks such as Angular, React, or Vue.js.</li><li>Experience with DevOps practices and tools such as Docker and CI/CD pipelines.</li><li>Knowledge of SQL Server and / or PostgreSQL for database design and management.</li><li>Hands-on experience with Kubernetes for container orchestration and management.</li><li>Experience with cloud platforms such as Azure, AWS, or GCP.</li><li>Minimum of 5 years of related work experience in software development using .NET technologies.</li></ul>

Responsibilities: <ul><li>Design, develop and deploy process automation workflows to support Smart Factory operation.</li><li>Extract, transform and analyze data into accurate, meaningful and actionable reports to support operational and business decision making, such as yield reports with data visualizations and recommendations.</li><li>Play a role as a bridge between business, IT and vendor(s) to support new loaders, functionalities and enhancements for Yield Management System such as Discover Yield tools, Tableau dashboards as well as Advanced Yield Examination internal tools.</li><li>With Product and Process knowledge, ensure data integrity for YMS tools.</li><li>Combine statistics, machine learning and computer science to turn data into actionable insights for solving complex process issue(s).</li><li>Design, build and maintain Predictive AI Models to enable proactive decision-making.</li></ul> Requirements: <ul><li>Bachelor’s Degree in Computer Science or&nbsp;Electronic/Electrical Engineering, with min. 2 years’ experience in Data Analytics field.</li><li>Proficiency in SQL and experience working with relational databases.</li><li>Strong working knowledge of statistics and its applications.</li><li>Experience in building automated reports.</li></ul>

Responsibilities: <ul><li>Lead the design, development, and deployment of machine learning models using Python for applications including process optimization, predictive analytics, demand forecasting, computer vision, and decision support systems</li><li>Network across manufacturing, R&amp;D, commercial, and business functions to identify and collaboratively execute on high-impact challenges solvable through machine learning techniques</li><li>Build production-ready ML solutions within enterprise platforms (Databricks, Azure ML) including model training, endpoint deployment, and monitoring</li><li>Develop and maintain scalable, modular, well-documented code following MLOps best practices including version control, logging/metadata standards, and CI/CD principles</li><li>Lead code reviews, architectural discussions, and knowledge sharing to maintain high quality, production-ready deliverables across the team</li><li>Collaborate with domain experts and stakeholders across a wide variety of domains to understand needs, integrate ML solutions into workflows, and deliver measurable business value</li><li>Communicate complex machine learning methodology, results, and business impact clearly to technical and non-technical audiences through presentations, documentation, and visualizations</li><li>Stay current with advancements in machine learning, and apply them to solve business challenges</li><li>Mentor and provide technical guidance to data scientists, helping to grow the teams capabilities in Hyderabad</li><li>Support ML governance processes including architecture and methodology reviews, risk assessments, and compliance with enterprise standards</li><li>Lead project planning and execution, managing timelines, resources, and stakeholder expectations</li></ul> Requirements: <ul><li>Masters or Ph.D. in a relevant field such as Data Science, Statistics, Mathematics, Computer Science, Operations Research, or a domain-focused field (Engineering, Chemistry, Economics, Finance, etc.)</li><li>5-8+ years of experience in data science, machine learning, or a related field with demonstrated impact</li><li>Strong foundation in statistical and machine learning theory with proven ability to select, apply, and evaluate appropriate techniques for complex, real-world problems</li><li>Extensive hands-on experience building predictive models and deploying them to production environments using Python</li><li>Proficiency with modern ML frameworks (scikit-learn, XGBoost/CatBoost, TensorFlow/PyTorch) and data manipulation libraries (pandas, polars, numpy)</li><li>Experience with solution architecting and design for ML systems</li><li>Hands-on experience with cloud platforms such as Azure and/or Databricks for deploying and managing ML models and solutions</li><li>Experience with version control (Git), collaborative development, and code review processes</li><li>&nbsp;Strong written and oral communication skills with ability to present technical concepts and results to diverse audiences from technical teams to business leadership</li><li>History of project leadership and driving initiatives from conception to production</li><li>Strong problem-solving skills and the ability to work independently as well as lead and mentor team members&nbsp;</li></ul>

Responsibilities: <ul><li>Develop and execute a clear, actionable, and time-bound analytics roadmap, outlining key milestones, resources, and timelines to achieve payment analytics objectives.</li><li>Lead the design and delivery of comprehensive analytics across all payment channels, products, and features, providing end-to-end visibility into the payment lifecycle.</li><li>Identify, assess, and bridge data gaps by collaborating with business, technology, operations, and data engineering teams to ensure complete, accurate, and timely payment data capture.</li><li>Translate complex payment data into actionable insights and strategic recommendations that optimize the payment process, improve customer experience, and drive business growth.</li><li>Partner closely with Tech &amp; Ops Payments, Product Analytics, Payment Train, Customer Experience, and other key stakeholders to embed analytics into decision-making at all levels.</li><li>Build, mentor, and manage a high-performing analytics team, fostering a culture of innovation, accountability, and continuous learning.</li><li>Cultivate and maintain strong relationships across teams to effectively communicate analytics value and drive enterprise-wide adoption.</li><li>Support regulatory review and governance</li><li>Promote advanced analytics practices, including proof-of-concept initiatives, to keep the organization at the forefront of payment analytics capabilities.</li><li>Lead internal initiatives, perform other duties and/or special projects, as assigned</li></ul> Requirements: <ul><li>Degree in Statistics, Mathematics, Economics, Engineering, or any other quantitative streams with 10+ years of hands-on relevant analytics/data science experience, or in lieu of a degree 12+ years of relevant analytics/data science experience.</li><li>8+ years of hands-on Experience in SQL /SAS with proven ability to leverage advanced algorithms and be efficient in handling complex/large data;</li><li>3+ years of experience in BI tools, e.g. Tableau etc.</li><li>5+ years of experience in managing teams with ability to motivate team, drive change, create a culture of learning, innovation and recognition</li><li>Ability to solve complex technical and people-oriented problems with minimal supervision</li><li>Advanced proficiency in MS-Excel and MS-PowerPoint with superior data analyses and story boarding skills</li><li>Strong written/oral communication &amp; stakeholder management skills</li></ul>

Responsibilities: <ul><li>Lead, manage and setup tagging and cookies auditing tools for automating manually tested scenarios and user journeys into automated scripts/flows across multiple our client platforms.</li><li>Perform code audits on tag management systems for feature enhancements, run regression testing</li><li>Provide QA requirements, review &amp; validate implementation of analytical, marketing technologies, across our client digital platforms via tag management systems</li><li>Mentor and guide team members on QA tools and processes</li></ul> Requirements: <ul><li>2 to 5 years of hands-on experience on any one of the tools to set up automation like Observepoint across consumer-facing websites, identify &amp; report out test results</li><li>1 to 3 years of hands-on experience in JavaScript, HTML, CSS or web design with ability to independently deliver on basic JavaScript concepts, set up algorithms/define flows for quality analyst role (QA)</li><li>1 to 3 years working experience/knowledge in Tag management tools like Tealium, Adobe Launch, or Google Tag Manager</li><li>Working knowledge &amp; understanding of core concepts / metrics in retail finance</li><li>Problem solving mindset &amp; Self-starter</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain robust pipelines to collect, transform, and store data used in model monitoring workflows (e.g., scoring data, performance metrics, outcomes).</li><li>Build scalable data architectures to support real-time and batch monitoring, including data ingestion, enrichment, and retention practices.</li><li>Develop reusable monitoring components (e.g., performance drift detectors, threshold-based alerts, metric repositories) that support various model types and regulatory needs.</li><li>Integrate data pipelines with model lifecycle platforms, MLOps tools, and observability solutions to ensure seamless model performance tracking.</li><li>Partner with model risk and compliance teams to ensure data lineage, audit trails, and documentation are preserved and accessible for regulatory reviews (e.g., SR 11-7 compliance).</li><li>Collaborate with data scientists, model validators, and product managers to align monitoring data infrastructure with evolving model monitoring requirements.</li><li>Work closely with the model monitoring analytics and strategy monitoring analytics teams within MO&amp;A to ensure the monitoring data infrastructure adapts to changing analytics and monitoring needs. Enable visualization and reporting capabilities through dashboards (e.g., Power BI, Tableau) that summarize model health, stability, and issue alerts.</li><li>Designing and maintaining high-performance data pipelines that ingest, transform, and version datasets for Model and Strategy Monitoring</li><li>Optimize data storage and compute performance for large-scale monitoring use cases involving high-frequency scoring or model ensembles.</li></ul> Requirements: <ul><li>Bachelor’s degree in a quantitative, technical, or data-focused field (e.g., Statistics, Mathematics, Computer Science, Data Science, Engineering) with 5+ years’ experience or in lieu of degree, and 7+ years of relevant work experience in, data engineering or related roles in the financial services or regulated analytics domain.</li><li>Strong proficiency with data engineering tools and frameworks (e.g., Apache Spark, Airflow, Kafka, dbt, PySpark).</li><li>Proficient in programming languages such as SAS, Python, and SQL for building monitoring pipelines and validation checks.</li><li>Experience with cloud-based data infrastructure (e.g., AWS, Azure, GCP) and data warehousing (e.g., Snowflake, Redshift, BigQuery).</li><li>Familiarity with MLOps practices, model metadata tracking (e.g., MLflow), and monitoring toolkits (e.g., Evidently AI, Why Labs, Prometheus).</li><li>Understanding of model risk governance requirements and the role of data engineering in ensuring compliant model monitoring.</li><li>Ability to work in an agile environment and deliver high-quality, production-grade code in collaboration with DevOps and platform engineering teams.</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain robust, scalable, and secure web applications.</li><li>Utilize Object-Oriented design principles and best practices to ensure high-quality software.</li><li>Write clean, efficient, and well-documented code in C# with both .NET Core and .NET Framework.</li><li>Ensure adherence to Web Standards (XML, JSON, HTML, CSS, APIs, Web Services).</li><li>Create and manage CI/CD pipelines using tools like Jenkins, GitLab CI, or Azure DevOps.</li><li>Automate repetitive tasks in the software development lifecycle, including builds, testing, and deployments.</li><li>Configure and maintain infrastructure for CI/CD pipelines, including servers and containerized environments.</li><li>Leverage cloud platforms like AWS, Azure, or GCP for scalable infrastructure and application management.</li><li>Incorporate DevOps principles to foster collaboration between development and operations teams.</li><li>Integrate unit testing frameworks (e.g., NUnit) into pipelines to ensure robust software quality.</li><li>Utilize test-driven development practices to enhance software reliability.</li><li>Work closely with developers, QA engineers, and operations teams to streamline workflows and address feedback.</li><li>Demonstrate strong communication skills to present ideas, solutions, and progress effectively.</li><li>Monitor CI/CD pipeline execution and troubleshoot issues promptly to minimize downtime.</li></ul> Requirements: <ul><li>Demonstrated knowledge of software application development (certifications and experience considered in lieu of a degree).</li><li>6+ years of experience in software development using C# and .NET.</li><li>5+ years of experience in developing .NET applications, including .NET Core and .NET Framework.</li><li>Proven experience in building enterprise-level web applications.</li><li>Strong background in Object-Oriented design and development.</li><li>Advanced JavaScript experience, including closures and prototype inheritance.</li><li>Proficiency in SQL (DDL and DML) and experience managing database structures.</li><li>Solid understanding of Web Standards (XML, JSON, HTML, CSS, APIs, Web Services).</li><li>Demonstrated use and knowledge of design patterns and cloud-native technologies.</li><li>Experience with Agile methodologies and iterative development processes.</li><li>Proficiency in CI/CD tools such as Jenkins, GitLab CI, Azure DevOps, or AWS Code Pipeline is required.</li></ul> Preferred work experience and skills: <ul><li>Strong proficiency in C#, JavaScript, and scripting languages like Bash, Python, or PowerShell for task automation.</li><li>Expertise in popular CI/CD platforms like Jenkins, GitLab CI, Azure DevOps, or AWS Code Pipeline.</li><li>Deep understanding of Git and branching strategies for effective code management.</li><li>Familiarity with unit testing frameworks like Unit, JUnit to integrate automated testing into pipelines.</li><li>Knowledge of cloud platforms like AWS, Azure, or GCP for scalable infrastructure management.</li><li>Familiarity with containerized environments (e.g., Docker, Kubernetes) and microservices architecture.</li><li>Exceptional problem-solving and analytical skills.</li><li>Strong communication and collaboration abilities.</li><li>Self-motivated and able to work independently with minimal supervision.</li><li>Detail-oriented with excellent organizational skills.</li></ul>

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37 sql Jobs found

Master Data Manager

SAP Basis Engineer

Manager, Data Engineering

Sr. Software Engineer - Ag & Trading .Net

Data Engineer, Senior

Senior Data Scientist - Machine Learning

VP - Payment Analytics

Manager, Quality Assurance - Digital Analytics (L09)

AVP – Model Ops Engineer

Senior Software Engineer 1 (.Net)

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37 sql Jobs found

Master Data Manager

SAP Basis Engineer

Manager, Data Engineering

Sr. Software Engineer - Ag & Trading .Net

Data Engineer, Senior

Senior Data Scientist - Machine Learning

VP - Payment Analytics

Manager, Quality Assurance - Digital Analytics (L09)

AVP – Model Ops Engineer

Senior Software Engineer 1 (.Net)

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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